Dr. Junming Li, Shanxi University of Finance and Economics, China
Dr. Junming Li, an Associate Professor at the School of Statistics at Shanxi University of Finance and Economics, holds a Ph.D. in Geodesy and Survey Engineering from the Chinese Academy of Sciences, complemented by degrees from Tongji University. His research expertise focuses on Bayesian statistical methods and their applications, particularly in geospatial analysis and big data scenarios. Dr. Li leads significant projects on pollution and carbon reduction, funded by the National Social Science Fund of China, showcasing his leadership in managing complex research initiatives. His contributions to textbooks and scholarly works underscore his commitment to advancing statistical knowledge and education.
Professional Profile:
Suitability for the Award
Dr. Junming Li is an excellent candidate for the Research for Best Researcher Award. His work is at the intersection of statistics, environmental science, and public health, making significant contributions to both academic research and practical applications. His leadership in several high-impact research projects, coupled with his extensive publication record, demonstrates his commitment to advancing knowledge in his field.
Academic and Professional Achievements:
Dr. Li holds a Ph.D. in Geodesy and Survey Engineering from the prestigious Chinese Academy of Sciences, along with a Master’s and Bachelor’s degree from Tongji University. His solid academic background has laid the foundation for his research in geospatial analysis and statistics.
As an Associate Professor at the School of Statistics at Shanxi University of Finance and Economics, Dr. Li has been actively involved in both teaching and research, guiding students and contributing to the academic community through his expertise in Bayesian statistical methods and their applications.
Leadership in Research and Project Management:
Dr. Li is currently leading several significant research projects, including a study on pollution reduction and carbon reduction in China’s counties, funded by the National Social Science Fund of China. His role as the Principal Investigator in these projects demonstrates his leadership and ability to manage complex, multidisciplinary research endeavors.
His ongoing work on Bayesian statistical methods for complex spatiotemporal processes in big data scenarios highlights his innovative approach to tackling contemporary statistical challenges, further solidifying his reputation as a leading researcher in his field.
Publications and Scholarly Impact:
Dr. Li has contributed to key textbooks and scholarly works, including chapters in national textbooks and the authorship of a book on Bayesian Statistics. His ongoing efforts to write and publish works in this area indicate a continuous commitment to advancing knowledge and education in statistics.
Publication Top Notes:
-
Title: Spatiotemporal Evolution of Global Population Ageing from 1960 to 2017
-
Citations: 124
-
Year: 2019
-
Title: A Practical Split-Window Algorithm for Retrieving Land Surface Temperature from Landsat-8 Data and a Case Study of an Urban Area in China
-
Title: Globally Analysing Spatiotemporal Trends of Anthropogenic PM2.5 Concentration and Population’s PM2.5 Exposure from 1998 to 2016
-
Title: Assessing Impacts and Determinants of China’s Environmental Protection Tax on Improving Air Quality at Provincial Level Based on Bayesian Statistics
-
Title: Spatiotemporal Evolution of the Remotely Sensed Global Continental PM2.5 Concentration from 2000-2014 Based on Bayesian Statistics